Sometimes words or phrases are coined that seem very apposite in that they appear to capture the essence of a thing or concept and quickly become a shorthand for the phenomenon. ‘Digital twin’ is one such term, increasingly appearing in both popular and academic use with its meaning seemingly self-evident. The idea of a ‘digital twin’ carries connotations of a replica, a duplicate, a facsimile, the digital equivalent of a material entity, and conveniently summons up the impression of a virtual exact copy of something that exists in the real world.
For example, there was a great deal of publicity surrounding the latest 3D digital scan of the Titanic, created from 16 terabytes of data, 715,000 digital images and 4K video footage, and having a resolution capable of reading the serial number on one of the propellors. The term ‘digital twin’ was bandied around in the news coverage, and you’d be forgiven for thinking it simply means a high-resolution digital model of a physical object although the Ars Technica article hints at the possibility of using it in simulations to better understand the breakup and sinking of the ship. The impression gained is that a digital twin can simply be seen as a digital duplicate of a real-world object, and the casual use of the term would seem to imply little more than that. By this definition, photogrammetric models of excavated archaeological sections and surfaces would presumably qualify as digital twins of the original material encountered during the excavation, for instance.
For example, Shanks draws a sharp distinction between the stop motion creations of Harryhausen and computer-generated imagery in the way that the technique of stop motion animation never quite disappears into the background which is part of both its charm and effect, unlike the emphasis on photorealistic models in CGI.
In CGI the objective is often to have the imagery fabricated by the computer blend in so one doesn’t notice where the fabrication begins or ends. The rhetorical purpose of CGI is to fool, to deceive. Harryhausen’s models don’t look “real”. More precisely, they don’t look “natural”. No one need be fooled. One admires the craft in their making. (Shanks 2020)
If a visualisation is to be perceived as realistic, is it increasingly required to respond to the viewer’s actions? Is static visualisation becoming old hat? Has interactivity become a necessary part of engendering perception, action, and emotion in our response to a visualisation? And what do we mean by interactivity?
Of course, interactivity may take various forms. For instance, it may entail navigation facilities: an ability to change the viewpoint, to move through the visualisation. It may also entail manipulation facilities: the ability to modify the visualisation, to move and re-organise elements. But what are we actually interacting with?
Evidently we see a visual representation or simulation of an environment so we are interacting with that simulation. But this implies a single interface, between us as the physical embodied viewer/actor and the visualisation. Indeed, Virtual Reality is characterised as the transparent invisible interface which is all-encompassing and three-dimensional; the user is surrounded by an immersive, total simulation in which the interface both disappears and becomes the experienced simulation at one and the same time (Pold 2005). But is this true?
Visualisation is much in vogue at present, especially with the increasing availability and accessibility of virtual reality devices such as the Occulus Rift and the HTC Vive, plus cheaper consumer alternatives including the Google Daydream and Sony’s Playstation VR, and there’s always Google Cardboard. We’re told that enhancing our virtual senses will increase knowledge, especially when we move into a virtual world in which we are interconnected with others (e.g. Martinez 2016), and the future is anticipated to bring sensors that go beyond vision and hearing and transmit movement, smells, and textures.
Hyperbole aside, we generally recognise (even if our audiences might not) that our archaeological digital visualisations are interpretative in nature, although how (or whether) we incorporate this in the visualisation is still a matter of debate. However, we understand that the data we base our visualisations upon are all too often incomplete, ambiguous, equivocal, contradictory, and potentially misleading whether or not we choose to represent this explicitly within the visualisation. I won’t rehearse the arguments about authority, authenticity etc. here (see Jeffrey 2015, Watterson 2015, Frankland and Earl 2015 (pdf), amongst others).